{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comparison of two means (T-test)\n",
    "\n",
    "BROKEN EXAMPLE, NEEDS TO FIX SOMETHING WITHIN BAMBI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:23:32.893304Z",
     "start_time": "2019-04-13T18:23:32.849988Z"
    }
   },
   "outputs": [],
   "source": [
    "import arviz as az\n",
    "import bambi as bmb\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "az.style.use(\"arviz-darkgrid\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook we demo two equivalent ways of performing a two-sample Bayesian t-test to compare the mean value of two Gaussian populations using Bambi."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate data\n",
    "\n",
    "We generate 160 values from a Gaussian with $\\mu=6$ and $\\sigma=2.5$ and another 120 values from a Gaussian'\n",
    "with $\\mu=8$ and $\\sigma=2$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:16:34.291525Z",
     "start_time": "2019-04-13T18:16:34.260418Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "a = np.random.normal(6, 2.5, 160)\n",
    "b = np.random.normal(8, 2, 120)\n",
    "df = pd.DataFrame({\"group\": [\"a\"] * 160 + [\"b\"] * 120, \"value\": np.concatenate([a, b])})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
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       "      <td>b</td>\n",
       "      <td>4.601657</td>\n",
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       "</table>\n",
       "<p>280 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    group      value\n",
       "0       a   9.811423\n",
       "1       a   9.007781\n",
       "2       a   5.128706\n",
       "3       a   0.797659\n",
       "4       a  10.317548\n",
       "..    ...        ...\n",
       "275     b   9.832355\n",
       "276     b   7.679154\n",
       "277     b   9.520645\n",
       "278     b   5.486694\n",
       "279     b   4.601657\n",
       "\n",
       "[280 rows x 2 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "  group      value\n",
       "0     a   9.811423\n",
       "1     a   9.007781\n",
       "2     a   5.128706\n",
       "3     a   0.797659\n",
       "4     a  10.317548"
      ]
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     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/tomas/oss/bambinos/bambi/.pixi/envs/dev/lib/python3.13/site-packages/arviz/plots/backends/matplotlib/violinplot.py:65: UserWarning: This figure was using a layout engine that is incompatible with subplots_adjust and/or tight_layout; not calling subplots_adjust.\n",
      "  fig.subplots_adjust(wspace=0)\n"
     ]
    },
    {
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U1KTs7GwVFBSoqalpytcODg7qk5/8pPbv368rrrhC11xzjQ4cOKB/+7d/09atW/X000/L5/PN6Lpbt27V3/3d3ykpKUnXXHON0tPT9dJLL+krX/mKmpqa9PnPf36ubw1AiASDRjVH2e0eM9PRKb2xVVq+3Cg7i4EMAABTOXPa/EQgyrR5ALB/BgammdZ/Zjcq0/rxbnMOS++77z5VVlaqtLRUP/rRj/Sd73xnytc++uij2r9/v2655Rb9t//2304df+CBB/Twww/r0Ucf1d///d+f95pjY2O68847ZVmWnnrqKS1btkySdNttt+mmm27Sgw8+qA996EOqqqqa69sDMEfDw/YmTt09TleCWDISkHbuZFo+AACSNDpqzg5ET06jZ9o8AMzcpGn9HZOfm5jWPxGepqWd7kqlGzWxzDksvfzyy2f0OmOMnn32Wfl8Pt12222Tnvsv/+W/6Mknn9TPf/5zbd68+bw3xW+88Ybq6+u1adOmU0GpJPn9ft1666360pe+pOeee07/9b/+19m/IQAh09ZmtG+/NDrmdCWIRWdOy79omeGTXgBA3BseNuofkAZPBqMTASldogAQflNN6z9zk6k0n+RLO92RmpTEPUo8itgGT7W1tWpra9OGDRvOmmqfnJys1atX649//KPq6urO2xG6bds2SdKGDRvOeu6KK66Y9BoAkRcMGh06LDU0Ol0J4kFHp/TGNuniZUa5uQxGAACxzRijoSE7CO0fOBmIngxFWUsUAKLPmd2o7e96zus18k+Ep37Zf08T+y/EuIiFpXV19mKFUwWhlZWVp153vrC0trZ20vecKTMzU9nZ2aeuByCyBgbsafd9/U5XgngSCEi73pKqKo0WzGcaDAAg+p0rFO3vt0PRYNDp6gAAoRAISJ0BqbNr8nFvkt2J6k8jRI1FEQtL+/rsPuapdryfOD7xuun099spTHp6+pTnamlpmfYcmZmZcrlc570WgJlraBzX3r1jChr7FwGm53af/ntaWppSUvhHO5/2E9LoqKVVq5KU5mOgAQDTYbwbOYGAUW+fUV+fUV9vUL19Rv39RuPnCEVTUyNfH+AUxrtIZIFRqbPbfkxI9krp6S6lp1unH35Lbjf3NtEkYmFptOnpYbcZIFTGxuy1SVvbnK4ktgwPD5z6+8DAAFPvZmhgQGptlZYukYqKGFQAoZKdne10CQgxxruhZ4y90VJfn90l2nfywZqiwLkx3gUmGxg4uwvVkr2JlN9vPzLSpfR0sWdDmMxkzBuxsHSiC3SiK/TdztcteqbzdaH29/fP6DwA5q6nx2jPXmloyOlKkEjGxqU9e6WOTqPFiySPh4EEACC0xsftYLS31w5Ee3vt6fRMoQcAhJLRyU39Bic3IHmTjNJPBqfp6XaImpqq826KjrmLWFg6sb7oxHqj7zaxxui51iF9t4k1Tevq6nTxxRdPeq6np0ddXV265JJLLrxYAOdljFFtnVRTY/9wB5xwvFnq7paWLzfKSGfQAAC4MOPjRv39Uk+v3TXa2ycN9DPGAQA4JzBqb3bb0Xn6mMctpafbIWpmhpSRIflYnizkIhaWVlVVqaCgQLt27dLg4KB8Pt+p50ZGRrRjxw4VFBTMKCxds2aNfvjDH2rLli265pprJj332muvSZLWrl0b2jcA4JSREaN39p49fQBwwuCQtH27tLDaqKKCgQIA4PwGB426e6TeHjsg7e+XgiSjAIAoNzYudXXbjwlJHqOMk8FpVqb9JxtJzU3EVny3LEs33nijBgcH9fDDD0967oc//KF6enp04403TmonHh0dVU1Njerr6ye9fv369SovL9cLL7yg/fv3nzre39+vRx55RB6PRzfccEN43xCQoE6cMHpjK0EpokvQSAcPS2++ZTQywt0uAOC0YNCoq9voWK3RW28b/fufjV57Xdq7T2posrtICUoBALFqdMzuPj1WK735tvTnV6XX/mK0d59RU5PR4CC/5GZrzp2lzz77rHbu3ClJOnTo0Klj27ZtkyRt3LhRGzdulCTdcsstevnll/Xoo49q//79uuiii3TgwAG98sorWrp0qW655ZZJ525tbdXVV1+t0tJSvfzyy6eL9nh033336ZZbbtEnPvEJXXvttfL7/XrppZfU2NioO+64Q/PmzZvrWwNwhvFxo8NHpIZGpysBpnaiQ3pjm3TRMqO8XD5NBYBEFAwa9fRKXZ32h7s9vawzCgBILIND9uN4s/2112uUlSnl5Eg52VJaGvdK05lzWLpz5049//zzk47t2rVLu3btkiSVlpaeCkt9Pp+eeOIJPfTQQ/rd736nbdu2KS8vT5/5zGd0++23T5qafz7r1q3T008/rQceeEAvvviiRkdHVV1drS9+8Yu6/vrr5/q2AJyhv9/exGmK/dmAqBIISG++JVVWGC2YL7ndDAQAIN4NDhp7XbcOOyBlx20AAE4LBKS2dvshSSnJRrm5Ul6uHaCyYe5kljEmIftxu7qYQwycjzFG9fXSkRqmp4XD8PCAbv5UhSTpsSfqlZKS5nBF8cefJl18kZTO5k/AeWVnZztdAkIsnse7xhj19Ejt7VL7CXsHYQDRh/EuEP0sSdnZUn6+VJAvpaTE973TTMa8EdvgCUBsYRMnxIP+AWnbdql6gVFFhSatiw0AiD29vUbNLVJrqzQScLoaAABin5F939/ZJR08JGVlGhUWSIWFUnJyYt4/EZYCOEtrm9H+/fZC0UCsCxrp0BF70fNlS03cf1IKAPFmZMSotVVqamZJIAAAwq27x34cOizl5xsVF0l5eZLLlTj3US6nCwAQPUZHjd7Za7R7D0Ep4k9Hp/TGVqm5mTUlACAW9PfbO/lueU06eJigFIg1IyODevih2059/fBDt2lkhDUzgFhhZK9x+vYeactr0rFao7GxxLiXorMUgCS7m/TAQXvhZyBejY5J7+yTWlqNli6J//V4ACAWDQ4aHamRWtucrgTAXHz/kb/Xtq2/PvX1tq2/1vfdHt3xpUcdrArAhRgJ2HuZ1NVJlZVGFeXxvZEuYSmQ4AIBOyTlhgSJ5ESH9Pob0qJFRqUl8ftLHgBiiTFGtXXS0aNsLAnEukBgWDu2v3jW8R3bX1QgMCyvN8WBqgDM1eiYHZo2HZcuWmqUnR2f91JMwwcSWEur0etvEJQiMY2NS/v2S7veNBoe5q4cAJw0Omq0c5d9A0ZQCsS+7u42jY4On3V8dHRY3d3cfACxbmhI2rFLOnosPn9p01kKJKDhYbubtP2E05UAzuvolP7yhlQ936i8XLKs+Px0FACi1eio0a43pd4+pysBAACzUXNUCgaNqhfE1z0UYSmQQIwxamiQjhyVxsedrgaIHuPj9uYhzS3S0qVGGenx9cseAKLZvv0EpQAAxKpjtZLfb1RUGD/3UEzDBxJEV7fRG9vsQIigFDi33j5p6zZp/wGj0dH4nFICANFkcNCord3pKgAAwFzU1jpdQWjRWQrEuZERe0fZ481OVwLEjsYmqa1dWlRtVFwcP5+QAkC06eh0ugIAADBXff32sjpJSfFx70RYCsSpYNCosdFeQ2SMTlJg1gIB6Z19UmOT0aKFUmZmfPziB4Bo4vU6XQEAAJgrl0tyu52uInQIS4E41NZmdPiINDjkdCVA7OvukbbtkIqLjBbMl1JTCU0BIFSysySXJQVZ+QQAgJiVky25XPFzn0RYCsSRri57yn13j9OVAPGnuUVqbZXKy42qKiWvN34GAwDgFK/XUkW5UW2905UAAIALYUlaMN/pKkKLsBSIA319dicp634B4RU0Ul291NQkVVYYVVRIHg+hKQDMxfz5Uk+v1NXtdCUAAGC2Fi2UMjLi656IsBSIYYODRkeP2R1vACJnbFyqOSY1NEnz5xmVlsTXtBMAiCS329KqlUZvvsXsGAAAYsmC+VJFRfzdBxGWAjFoZMTo2DGp6ThrfAFOCgSkAwftbtP584yKiyTLir/BAgCEm8dj6dJLjPbuk1rbnK4GAABMx2VJSxZLpaXxee9DWArEkJERo9o6qbGRkBSIJkND0t59Um2tHZoWFhKaAsBsud2WViyXGhuNDh6WgkGnKwIAAO+W5pOWXyylp8fv/Q5hKRADRkaM6uqlhkZuHIBoNjAo7dkrHauV5lURmgLAhSgrs5SZaXeZ9vU7XQ0AAJhQViotrI7/fRsIS4EoNjxsd5I2NdFJCsSS/gE7NK05Ks2bZ1RUyJqmADAb6emWLltr1NAgHa7hw2IAAJyU5pOWLZWyshLjnoawFIhCg4N2SNrcTEgKxLLBk9Pzjx6TqiqMStgICgBmzLIsVVRIBQVGBw9Jbe1OVwQAQGJxuaT586TKisS6jyEsBaJIf78dkra0SGSkQPwYGpL2HzwZmlbaoWm8T10BgFBJSbG0coXU2Wl06DBT8wEAiITiInvKfXJy4t23EJYCUaCr26iuTmo/4XQlAMJpJCAdPGyHpuXlRmWliTn4AIALkZNjT80/3iwdqZECAacrAgAg/mRlSosXSxlxvIHT+RCWAg4xxqi9Xaqrl7p7nK4GQCSNjtmBaW2dVFpsVFEh+XyJOxgBgJmyLEulJVJBvlHNUamxkdk4AACEQrJXqq6WSoq5LyEsBSJsfNyouVmqb7B3zgaQuIJBqaFJamyy1+SrqpQyMhicAMD5JCVZWrJYKi+zp+af6HC6IgAAYpPLJVVV2uuSslSYjbAUiJCREaPGJrsDIjDqdDUAoomR1NpmP7Iy7U7Tgny7gwoAMLW0NEuXrJI6OuxNoPggGgCAmSsskBYttNcHx2mEpUCY9fYa1dVLbW3sbA/g/Lp7pO49UkqyVFZmr2ualMTgBQCmk5trad1l9pjr6DG7cx8AAJxbmk9astheDxxnIywFwiAYNGprkxoaWY8UwIUZHrE3MDl6TCopNiovk/x+BjMAMBWXy9K8Kqm4yGj/AabmAwDwbi5LmjfPnnbvcnFvMRXCUiCEAoHTU+1H2KEVQAgEg/aapo1NUm6OHZrm5TFFHwCmkpJiT81vbDQ6eJguUwAAJLub9OKLE3uX+5kiLAVCoLfXqL5Bam1lqj2A8OnotB+pqVJ5qVFJCVP0AWAqZWWWsrKMdu9hLVMAQGIrKban3bvd3DvMBGEpcIGYag/AKUND0qEj0pGjTNEHgOn4/ZbWrrED045Op6sBACDyFlVLlZXcK8wGYSkwSyMjRk0np8Qy1R6Ak86cop+TbYem+flM0QeAM3k8llatNHrrbQJTAEBiWbrYnmmB2SEsBWaop8eooZGp9gCiU2eX/UhNkUpLjUpLJK+XgREASPYmFiuWG72xze7OBwAg3pWXEZReKMJSYBoTU+3rG6SeXqerAYDzGxqWjtRIR4/ZO0KXl0npLOIOAPJ4LFXPN9qz1+lKAAAIL49bWjDf6SpiF2EpcA4TU+0bmqQAU+0BxKBgUGo6bj+ys4zKy6UCpugDSHB5eU5XAABA+GVlsRHsXBCWAmfo7TOqr2eqPYD40tVtP1JTpPIyo9JSu8MKABKN2y25LMZ5AID4lpTkdAWxjbAUCc8Yo44Oqa7eXu8PAOLV0LB06Ig9Rb+kxKiyQkpJITQFkDj6+ghKAQDxr7vH6QpiG2EpElYwaNTcItXVSQODTlcDAJEzNm6vxdzQIBUWGlVWShmsawogATQ0Ol0BAADhNzQknegwystljH8hCEuRcEZHjRqb7JBghPVIASQwI6ml1X7kZNudprm5rGsKID41NBodb3a6CgAAImPvPmn1pUZpaYztZ4uwFAljaMiort7e7CQYdLoaAIgunV32w58mVVQYFRdJLhcDKwCxzxijY8ekmmNOVwIAQOQEAtKOndKKFUbZWYzrZ4OwFHGvr88OSVta7C4qAMDU+gekffulmhqpsoLNoADEtsFBo3377U3uAESex+PRnXfeqQ0bNmjLli267777nC4JSCiBUWnnTqmy0mj+PMntZlw/E4SliFu9fXYXQVu705UAQOwZCdibQR2rtTtNK8oJTQHEjvFxo/oGe0M7ZhQBzrnzzjt11113yeVy6aqrrnK6HCAhGUm1dVJ7u7RoEeuYzkTEw9LnnntO//iP/zjta9atW6fHHnts2tds3bpVn/70p6d8/plnntGqVasupETEuN4+o6NHpfYTTlcCTG1kZFAPP3Tbqa8ffug23b75ESUn+xysCjjb6JhUc1Sqryc0BRD9jDFqabF/bg0NO10NgA0bNsjlckmSXC6XNmzYoP0HHS4KSFADg9Kbb0m5OUbV1WzwOp2Ih6VLly7V7bfffs7nfve73+nw4cPasGHDjM+3du1arV279qzjRUVFF1wjYlN/v1HNUTpJERu+/8jfa9vWX5/6etvWX+v7bo/u+NKjDlYFTO3M0LSy0g5NmcYDIFqMj9shaV29fTMIIDps2bJFV111lVwul4LBoLZs2aLc/L92uiwgoXV0Sh3bpPw8o8pKsZ7pOTgSli5duvSs44FAQE8++aQ8Ho9uuOGGGZ9v7dq12rx5cyhLRIwZGrJD0uYWpysBZiYQGNaO7S+edXzH9hcVCAzL601xoCpgZkbHpCM1UkODNH+eUUkJG0EBcE4gYNTYKDU02RtZAIguE2uUnrlm6b9+j7AUiAbtJ+xHZoZRRYVUkM+4fkLUrFn6hz/8Qd3d3dq4caPy8vKcLgcxIBAwOnpMamqSguzchBjS3d2m0dGz5waOjg6ru7tNBQUVDlQFzM5IQNp/UKqtl6oXGBUVMrACEDn9/ac38GQcCESvsbEx3X333U6XAWAaPb3SnneklGSpvNyojA1eoycs/fnPfy5JuvHGG2f1fbW1tXr88cc1PDyskpISXX755crJyQlHiYgSwaDdQXD0mN3hBABwztCQPbhqaDBavEjKyEjsgRWA8BkbM2ptlY43S909TlcDAEB8GR6RDh+xl94qLDAqKZaysyXLSrzxfVSEpU1NTXr99ddVWFioK6+8clbf+8ILL+iFF1449XVKSoo2b96sW265JdRlIgp0dhodOMhaVAAQbbp7pK3bpdISo+oFktebeIMqAKFnjFFHhx2Qtp9gZ3sAAMItGLSXOWxusbtNiwqNioslvz9xxvdREZY+99xzCgaD2rRpk9xu94y+JycnR1/96lf1vve9TyUlJert7dXWrVv1L//yL/r2t78tv9+vm266acrvz8zMPLUrH6LfyIjRvv1jOt4clCwpLc3pioAL5/OlTvtcGv+BI4Z190hv75GWLPaoonxmv9MBhEcsj3e7u4M63hzU8ePjGjm5Fmnq1L8+AUQZxrtA/GjvsB+ZGZZKStwqKXYpJSW+g1PHw9JgMKjnnntOlmXpb/7mb2b8fQsXLtTChQtPfZ2amqrrr79eS5Ys0aZNm/Tggw/qYx/72JQDxJ4e5u7EiuZmo4OHmHKP+DE4ODTtcwMDAxGsBgiPN7ZKhw5JS5dIPl98D6biRXZ2ttMlIMRibbw7NGTU3GKvQ8osIiC2Md4F4s/AgD3Tw5KUkyMVF0n5+bG3vulMxryOh6Wvvfaajh8/rvXr16u8vHzO51u0aJFWrlypHTt2qK6uTvPmzQtBlXCC3U0qnehwuhIAwIXo7JJe3yotWmhUXhZbgygAkREMGrW1SU3H7Z8ZAAAguhlJHZ32w+OWCgvtTaHiae8Cx8PSC93YaToTKfHw8Nm7TSM2dHQYvbNPCgScrgQAMBfBoHTgoP1z/aJlUlJS/AyiAFy4vj67i7S5WQqMOl0NAAC4EGPj9geeTcclv9+otEQqKoz9/QscDUu7urr0xz/+UVlZWfoP/+E/hOScY2Nj2rdvnyzLUnFxcUjOicgxxujYManmmNOVAABCqf2EtHWbtGKFUUZ6bA+eAFyYiS7ShkZ2swcAIN7090sHD0mHD9vdpuVlUmZmbI77HQ1Lf/nLX2p0dFTXXXedvF7vOV/T2dmprq4uZWdnKycn59TxN998U6tWrZJlnf6HHxsb0/3336+mpiZdeeWVysrKCvdbQAiNjxvt3Se1tjldCQAgHIaGpe07pOUXGRUUxObACcDsjYwYNTRKTU10kQIAEO+CRvbskRYp3W9UWSEVFkouV+yM/x0NS3/xi19Imn4K/lNPPaWHHnpIt99+uzZv3nzq+Je//GVJ0iWXXKLCwkL19fVp+/btOnbsmEpKSnTPPfeEt3iE1NiY0VtvS13dTlcCAAinYFB6e4+0dLFRGeuYAnFtcNCots6eah80TlcDAAAira9femefdKRGqqwwKi2V3O7ovwdwLCzdvXu3Dh06pBUrVmjx4sWz/v6bbrpJr776qrZt26auri55PB5VVFTo85//vD73uc8pMzMzDFUjHMbGjN58i+lYAJBI9h+UjNj4CYhHgYDR0aNSY5O9CQQAAEhswyPSwcNSbZ20YL5RSYkmzRSPNpYxJiHHMF1dbLcZDcbH7aCUjlIkkra2em2+7ZJzPvfgw2+qoKAiwhUBzrlomVRSHL0DpUQysUEm4ocT492WVqODB5luDyQ6xrsAppOVad8H+HyRvw+YyZjXFYE6gCm9s5egFAAS2b590omOhPzcFogrxhgdPGS05x2CUgAAML3uHnvz12i9DyAshWPq6oza2p2uAgDgJCNp715peDg6B0oAZubgIam+wekqAABArBgbl956S+rqir77AMJSOKK3z+jwEaerAABEg8CoPdMgQVcGAmLe8LBRY6PTVQAAgFhjJNUcdbqKsxGWwhH797PgPwDgtK5u6Xiz01UAuBD9A4zrAADAhenrc7qCsxGWIuJaWo16o/B/BgCAs44etTf+AxBb0v2Si33aAADABcjMdLqCsxGWIqKMMToahS3WAADnDY9ITU1OVwFgtpKTLS1a5HQVAAAg1iR7pUULna7ibISliKiODmlg0OkqAADRqr6BtUuBWFReZmn5xZLH7XQlAAAgFqT7pdXvkfz+6Jue4nG6ACSWpuNOVwAAiGZDw1Jnp5Sb63QlAGarqNBSVqbRwUNSW7vT1QAAgGjkdktVlfbDFaXr+BCWImKCQaOOTqerAABEuxMdhKVArEpJsbRyhdTdbXSs1v7/GQAAwOOWSkulygp7CZ9oRliKiOnrk8bHna4CABDturudrgDAXGVlWbpklTQ4aNTUJB1vkQIBp6sCAACRlpkhlRRLRUWSxxPdIekEwlJETE+v0xUAAGKB/eGakdsdG4MpAFPz+SwtXChVVxt1dtrT89vapMCo05UBAIBw8fulwnw7IPX5Ym9MT1iKiBkYcLoCAEAsMJIGB6X0dKcrARAqlmUpN9deYmPJYqPuHqm9XTpxgs0/AQCIdZak7GwpP0/Ky4vNgPRMhKWImJERpysAAMSKkYBEVgrEJ8uylJ0lZWdJixbaU/U7O6WOTqmrSxodc7pCAHOVlVWgpKQUjY4OTzqelJSirKwCh6oCEEq+VCknR8rNsf+MlSn2M0FYiohhnSoAwEyN8jsDSBg+nyWfTyork4wx6uuzQ9POLnsN4zHWvAdijtebotVrPqzX//L8pOOr13xYXm+KQ1UBmIvUVPuDzuxsKSfb3tQxXhGWAgAAAIgKlmUpI0PKyJAqK0+Gp/1Sd5fU1W2Hp6x3CsSGL9z6gMbHx7Rt668lSWsvu05fuPUBh6sCMFNpPjsYzcq0/4zncPTdCEsRMS6X0xUAAGKFxe8MADoZnqZLGelSRYV9bHDQXvO0p0fq7pEG+u21jgFEl+Rkn267/eFTYelttz+s5GSfw1UBOBe32961PjPTDkczM6WkpMQJR9+NsBQR4/U6XQEAIFYk8zsDwBQmpu2XFNtfj43ZU/d7eu0Ata9PGhqe/hwAACQqS/Zu9ZmZ9kyOzAwpLc3+gBI2wlJEjDfJ6QoAALEiid8ZAGbI47GUnW1PEZwwMmIHqL29doja28f6+QCAxGPJDkLT0+1gNCPd/rvbTTA6HcJSREwSXUIAgBliNgKAuUhOtpScLOXlnT42MmLU22t3nvaeDFJHCFABAHHi3cFoerqU7o+vXeojhbAUEUOXEABgpvidASDUkpMt5edL+fmnj53ZgdrXzxR+AEBscFnvCkb9dIyGEmEpIiY1xekKAACxINnLmkkAIuNcHaiBgDnVfdp/MkAdGHSuRgBAYnO57Onzfv/pafR+v+RyMV4OF8JSRIyPjQ8BADOQluZ0BQASmddrKTdXys09fWxszNjB6cnwtK9P6h+QgkHn6gQAxB9v0unp8+kng1Gfj0aCSCMsRcT4fJLbLY2PO10JEB08Ho/uvPNObdiwQVu2bNF9993ndElAVEhPd7oCAJjM47GUlSVlZZ0+ZozRwMDp7tOJIDUw6lSVAIBY4ks9HYhOBKTJyYSi0YCwFBFjWZbS/UbdPU5XAkSHO++8U3fddZdcLpeuuuoqp8sBokYGYSmAGGBZlvx+eypkUdHp46fWQT3ZgdrbKw2POFcnAMBZluzfFROh6MSUejZeil6EpYio1FQRlgInbdiwQS6XS5Lkcrm0YcMG7T/ocFFAFGDZFgCxbKp1UN/dgTowIBnnygQAhIHbfXIK/UQ4miH501hfNNYQliKiMjOl5hanqwCiw5YtW3TVVVfJ5XIpGAxqy5Ytys3/a6fLAhzlsuxP2gEgnni9lnJypJyc08fGx82p8LS31+5EHegnQAWAWOFxn9yJPv30xkusLxofCEsRUdlZTlcARI+JNUrPXLP0X79HWIrElpnJJ+8AEoPbffY6qOPj9jqovb2nQ9T+filIggoAjkrynA5GJ8JRn48xa7wiLEVE+f2WvF6jQMDpSgDnjY2N6e6773a6DCCq5GQ7XQEAOMfttpSRYd+QTwgGjfoHpL6T3acEqAAQXhPB6Jldo6mpBKOJhLAUEZeVKbW1O10FACAaZROWAsAkLpeljJM366UnjwWD9hqoPb0np/D3Sv0DjpYJADHJ7bZ/vk6Eo3SMQiIshQMK8glLAQBnS/LY0/ABANNzuc7uQB0bs9dA7emVenrsAHV4xLkaASDaWJLS/FJmxslHppSWxhqjOBthKSIuN9fpCgAA0Sgnh/VKAeBCeTyWsrMnd+iPjBg7OO07HaCOjTtXIwBEUkqyHYhmnjGl3uNhrInzIyxFxHm9lvxphqlCAIBJmIIPAKGVnGypoEAqKLC/Nubk9P0eqbvH/nNwyNkaASAUXJYdiGZm2o+sTPtnIHAhCEvhiLxc1lUCAEyWx8wDAAgry7JO7eRcVmYfCwTs7tPubjtA7e1l8ygA0S/JI2VlnXxk2kEpM5QQKoSlcER+vlRb73QVAIBoke5nl1EAcILXayk/3x6fS9L4uFFvr9TVbQeoXd1SMOhggQAgKdlrz0LKzrIDUtYaRTgRlsIRmZn2+iEsOg8AkKTCQqcrAABIkts9ee3TYNAOTzu7CE8BRM5EOJpz8ucRO9QjkghL4QjLspSfZ9TQ5HQlAIBoUJDvdAUAgHNxuaxTU10lOzzt6bHD085Oe91TZu0DmKskz8lwNMcOSNPSCEfhHMJSOKaoSISlAACl+xkQA0CscLlOd54umC+NjRl1dUkdnXZ4OjDodIUAYoHLsmec5uTY69anpzOtHtGDsBSOycqylOYzDKgAIMGVlDhdAQDgQnk8k9c8HR426uiQTnRIXV3S6Jiz9QGIHr5UKTdHys21P3DxeAhHEZ0IS+GoinJp/0GnqwAAOMXjlkqKna4CABAqKSmWSkul0lLJGHvKfken1N4u9fU7XR2ASHK57Cn1eXl29yibeSJWEJbCUUVF0uEj0ti405UAAJxQXExXAQDEK8s6vd7pgvnSyIjRiRNS+wk7QGWjKCD+JHvtTvP8PLt71O1mnIfYQ1gKR3k8lkpLjerqna4EABBpluwZBgCAxJCcfLrrdGzMnOo4bW+neQKIZb5UqaDADkgzM1l7FLGPsBSOq6yQGhr5ZBkAEk1hoeTzMZgGgETk8VgqLJAKC6Rg0N4kqr1dam2XAgGnqwNwPhnpdkBakM9GnYg/joSl73//+9XUdO5t0D/+8Y/r3nvvndF5gsGgnn76aT3zzDOqq6uTz+fTZZddpi996UuqqqoKYcUIp+RkSxXlRrV1TlcCAIgUl2VPyQQAwOWylJtrb/qyeLFRd4/U2mqHp8MjTlcHYEJWph2OFhSw/ijim2Odpenp6br55pvPOn7xxRfP+Bxf//rX9bOf/UzV1dX65Cc/qY6ODv32t7/Va6+9pv/zf/6PqqurQ1kywmhelXT8uBQYdboSAEAklJXRVQoAOJtlWcrOkrKzpCWLpd5eo9ZWqbVNGhp2ujog8WRl2nuNFOTbjU5AInAsLM3IyNDmzZsv+PvfeOMN/exnP9Pq1av1k5/8RF6vV5L0kY98RJ/97Gd1991368knnwxVuQgzj8fS/PlGBw46XQkAINySPNL8eU5XAQCIBRkZljIypIULpZ4eo5ZWqaWVqfpAOGWkS8VF9pJJBKRIRDG7Zumzzz4rSbrjjjtOBaWStH79em3YsEGvvvqqjh07pnnzuBuLFWWlUlOT1NfvdCUAgHCqXiAlJTHwBgDMTmampcxMadHCk1P1W+zgdHTM6cqA2OdPk4qL7Q5SZv8g0TkWlgYCAT3//PNqbW1VRkaGLr30Ui1ZsmTG379161b5fD5deumlZz03EZZu376dsDSGWJali5YZbdsuBY3T1QAAwiEn294FGQCAC3XmVP1Fi4xOnJCaW6QTJ7iPAGbD67U7SIuKpIx0AlJggmNhaXt7u/7hH/5h0rErr7xS999/v3Jycqb93sHBQbW3t2vRokVyu91nPT+xuVNtbW2oykWEpKdbWrDA6PARpysBAIRakke6aJl9kwsAQCi4XJa9I3eBFAgYtbXZwWl3j9OVAdHJ5ZIKC6SiQntTNcZlwNkcCUs3bdqktWvXqrq6Wl6vVzU1NXrooYf0yiuv6NZbb9VPf/rTaf+H7evrkyT5/f5zPj9xvL9/6vncmZmZcrlcc3gXCJesLKORkTF1dAadLgUIC58vddrn0tLSIlgNEDmXrPKouPjsDzkBhAfjXSSiwkJp+XJpYMCo6fi4GhuDGhqm3dQpZ/Y2paWlKSWFca5TcrItlZW5VVToYjkk4DwcCUtvv/32SV+vXLlSP/zhD/XJT35SO3fu1J///Ge9733vC2sNPT181BjNqirtXS9HWLgdcWhwcGja5wYGBiJYDRAZ5aVSaoqlri6nK8FUsrOznS4BIcZ4F4kuP0/KyzXq7JSajkvt7UzTj7Th4dPj2oGBAY2PO1hMAvJ6pZJiqbTk9Dqk0/SUAQlhJmPeqPmo2eVyadOmTZKkXbt2Tfva9PR0SVN3jk4cn6rzFNEvOdnS8uUSn3cBQOzLypQWLXK6CgBAIrIsS7m5llYst3TlBmnxQnsjGyBeWbI/KFi1QrryCmlhtcWGTcAsObZm6blMpLtDQ1N3XUmSz+dTfn6+GhsbNT4+fta6pRNrlU6sXYrYlJ1laekSo30HnK4EAHChUlOkFcvtNeUAAHCS12upokKqqJB6eoyajtvrmwZZ/QtxIDXV7iAtKbabjwBcuKjpLJWk3bt3S5JKZ7BN7tq1azU4OHjOLtQtW7ZIktasWRPaAhFxpaWW5s9zugoAwIVI8kiXrGLADgCIPpmZlpYttfTeK6XFi+g2RWya6CK9ZJV0xXppXpXFuAsIgYiHpUeOHFFvb+9Zx3fs2KGf/OQn8nq9+uAHP3jqeGdnp2pqatTZ2Tnp9R/72MckSd/97ncVCJxe2PL111/Xli1btGbNGs2bR8oWDxbMt1R+/vwcABBF3G5p1UopLY0BOwAgenk8lirKLa1fZ2nNe+zOPPZFQ7RLTZEWzJeu3CCtWmkpL9diV3sghCI+Df/FF1/Uo48+qvXr16u0tFRer1eHDh3Sa6+9JpfLpXvuuUclJSWnXv/UU0/poYce0u23367NmzefOr5u3TrdeOONevbZZ3XDDTfove99rzo6OvTb3/5Wfr9fd999d6TfGsJo8WJ7Mfam405XAgA4H7dbumSllJXFoB0AEDuysixlZUkLq42am6XGJmlg0OmqAJslKTdXKiuV8vJEOAqEUcTD0ssuu0w1NTXat2+ftm3bpkAgoNzcXF199dX6zGc+oxUrVsz4XPfee68WL16sZ555Rk888YR8Pp+uuuoqfelLX6KrNM5Ylr1+qWXZgxYAQHTyuKVVq+x1pwEAiEVJSafXNu3qMqpvkNrbJeN0YUhI3iSppEQqL5NSUhhfAZFgGWMS8md+V1eX0yXgAtUcNTp6zOkqgAvX1lavzbddcs7nHnz4TRUUVES4IiA0vF57zayMdAbysWhio03ED8a7QOiMjBg1NEpNTVJg1OlqYsfw8IBu/pQ9tn3siXqlpLA47ExlpEsV5VJhIRtlAqE0kzFvxDtLgblaMN+S12t08CCf7gJAtPCl2kGpz8dgHgAQf5KTLVUvkOZVGbW0So2NUm+f01Uh3liyw9GyMmbpAE4iLEVMKi+zlJpqtGePNDbudDUAkNhysqUVy+1piwAAxDO321Jpib0RVG+vPUW/tdXeXwG4UMleOyAtLRG72QNRgLAUMSsv19Ka1UZv7ZaGhpyuBgASU3mptGgR08MAAIknI8PSxRfZG0I1Ntl7KwQCTleFWJKRLlVWSAUFjKWAaEJYipjm91tau9ronb1SR6fT1QBA4nBZ0uJFUlkZA3sAQGJLTra0YL49Rb+5Raqvl/oHnK4K0cqSlJ9vh6RZTLUHohJhKWKe12vpklVGR2qk2jqnqwHOLyurQElJKRodHZ50PCkpRVlZBQ5VBcxcsteeds8AHwCA01yu01P0OzqM6upp6MBpLpf930ZFOWu8A9GOsBRxwbIsLayWsrOM9u5jh0pEN683RavXfFiv/+X5ScdXr/mwvN4Uh6oCZiY3R7r4IvuDKgAAcG65uZZyc6W+Pjs0bWlhc9pE5fXaAWlZKeu7A7GCsBRxJS/P0mVrjfa8I3X3OF0NMLUv3PqAxsfHtG3rryVJay+7Tl+49QGHqwKmZklasECqqrQ/oAIAAOeXnm6va1q9wN4MqrFJGmeD2oSQ5rOn2hcV2RuDAYgdLqcLAEItJcXS6vdIC+bbN/dANEpO9um22x8+9fVttz+s5GSfgxUBU/OlSmvXSPOqLIJSAAAuQEqKpUULLV15hbRgnpRE21LcSvfbyxWtXyeVlloEpUAM4kc04pJlWZo/T8rLM9q3T+rrd7oiAIhNlRX2h08M9AEAmLukJEvz50sVFUZNTVJdvTQScLoqhEJWpjRvnpSXy5gJiHWEpYhrGemW1q4xOnpMqq1lnSAAmKnUVOmipVJ2NgN+AABCzeOxVFkplZUZHW+2Q9OhIaerwoXIzZHmVTFmAuIJYSninstlqXqBVJBvb/7UP+B0RQAQ3cpLpepq+0YOAACEj9ttqbxMKis1am2VjtVyvxIrCvLtTtKMdMZLQLwhLEXCyMiwN3+qrbUHIUHaTAFgkjSftHSplJ3FoB8AgEiyLEtFRVJhoVFbu3T0mNTPUmJRqajQ7iT1+xkvAfGKsBQJxeWy1wgqKjLaf0Dq7HK6IgBwnsuyOyOqKu2fkwAAwBmWZamwwJ4VR2gaXQhJgcRBWIqE5PNZes+l0vFmo8OHpcCo0xUBgDNyc6Qli+2fiwAAIDqcGZq2tklHj0oDg05XlZgK8u3NLglJgcRBWIqEVlJsKT/P6EiN1NjkdDUAEDnJXmnRIqmokIE/AADRyrIsFRVKhQVGLS1SzTE2goqUvFxpwQLWJAUSEWEpEl5SkqWlS6TSUqODB6XuHqcrAoDwcVlSRYU9jYwNnAAAiA2WZam42F7TtLHRnp4/OuZ0VeeXnOzT4sWXnfp7LEj3S4sXsbs9kMgIS4GTMtItrVktNTcbHT4ijQScrggAQis/T1q0kCn3AADEKpfLUkWFvQdDbZ3U0BDdG9dalqV7vvGbU3+PZinJdidpcVH01wogvAhLgXcpLraUn28PPurqonvwAQAzkeazp9zn5TLwBwAgHni9lhYtlMpK7UaPtnanK5patAePbre9yWVlheR2R3etACKDsBQ4B4/HUvUCqbTEHny0tjldEQDMnjfJ3uW+rJRd7gEAiEc+n6WVK6Tubvu+hSXFZs6SPUaaN09KTmacBOA0wlJgGqmpllYsl3p6jA4dZvABIDa4LKmi3B78sy4pAADxLyvLXlKspcW+b2FJsellZ0lLFrPDPYBzIywFZiAz0x58tLYZHTkiDbIDJYAoVVwkLZhvf9gDAAASS1GRpbw8o5qj9nqmrCg2mdcrLV5o/zsBwFQIS4FZKCywlJ9ndPy4VHNMCvCJLYAokZsjVVfbm9UBAIDE5fFYWrxIKi422r9f6u1zuqLoUFYqVS+QkpIYKwGYHmEpMEsul6WyMnsHyoZGexOo0TGnqwKQqLIy7U7SnBwG/gAA4LSMdEtr1xg1NEiHa6Rg0OmKnJHmk5YulbKzGCsBmBnCUuACeTyW5lXZO1DW1Uv1DdL4uNNVAUgU6X47JM3PZ+APAADOzbIsVVRIeXlG+/ZLXd1OVxQ5lqTKSmn+PHa5BzA7hKXAHCUlWapeIFWUG9XWSQ2NifupLYDwS/NJ8+dLhQX2DRAAAMD5+HyW3nOpUWOTdPhI/Dd5+NOki5ZJGRmMlQDMHmEpECJer6VFC6XKCqNjtVJTkxRkRXUAIeJLtTsjiooISQEAwOxZlqXyMik3x2jvPqm7x+mKwqOywp59QzcpgAtFWAqEWHKypSWLpapKu9OU0BTAXPhSpaoqqaSYkBQAAMydz2dp9XuMjh6Tjh2T4uVWJdlrd5Pm5jJeAjA3hKVAmKSk2KHpvCp7TVOm5wOYDX+aNK9KKiwkJAUAAKFlWZYWzJeyMo3e2SsFRp2uaG6ys6TlF9uNKwAwV4SlQJglJ9vT86sq7dC0sVEai/M1ggBcuHS/NG+eVJBPSAoAAMIrN9fS2jVGb70t9Q84Xc2FKSuVFi+SXC7GTQBCg7AUiBCv19LCajs0bWiwO01j/RNcAKGTlWmHpHlMHQMAABGUmmppzWqj3Xukjk6nq5mdRdVSZSVjJwChRVgKRFhSkqX586WKCqPjx6XaOmkk4HRVAJySm2NPt8/OZqAPAACc4fFYWrXSaP8B6Xiz09Wcn8uSLr5YKixg/AQg9AhLAYd4PJYqKqSyMqPmZqmuXhoYdLoqAJFgSSoosDduykhnkA8AAJznclm6aJnk8RjVNzhdzdRcLumSlVJODmMoAOFBWAo4zOWyVFoqlZQYnThhd5p29zhdFYBwcLmk0hKpotzeiRYAACDaLF5kKRg0amxyupKzWZJWriAoBRBehKVAlLAsS/n5Un6+1NVtVFcntZ9wuioAoeBNksrKpPIye/1iAACAaLZksTQ8LJ3ocLqSyZYtY313AOFHWApEoewsS9lZ0sCAPQXmeLMUDDpdFYDZ8qVKlRVScbHkdjOwBwAAscGyLC2/2GjrNmlwyOlqbBXlUkkx4ykA4UdYCkSxtDRLS5dIC+bb02AaGqUAm0EBUS8n2x7Q5+XZNxsAAACxxuOxtHy50fbtUtA4W0u6X1pY7WwNABIHYSkQA7xeS/PnSVWVRq2tdmja0+t0VQDO5HJJxUX2VPt0Nm0CAABxICPd0sKFRgcPOVeD2y2tWG7v9QAAkUBYCsQQl8tScbE9pbe7256i39YmOfxBL5DQkr32eqRlpaxHCgAA4k95mdTUJPUPOHP9qgo2xgQQWYSlQIzKyrKUlSUNDRk1NNoDmLFxp6sCEke6316PtLCQTgcAABC/LMvS/PlGu/dE/treJKmiIvLXBZDYCEuBGJeaamnRQmn+PKPmFqm+PnoWYQfijSUpP98etGdnEZACAIDEUJAvpaZIQ8ORvW5Jsb12KgBEEmEpECc8HkvlZVJZqVFHh1TfIHV0Ol0VEB+SPFJJiT0NLTWVATsAAEgslmWppNio5lhkr1tSEtnrAYDkQFja2tqqF198Ua+88oqOHj2qEydOKDMzU5deeqluueUWrVy5ckbn2bp1qz796U9P+fwzzzyjVatWhahqIHZYlqW8PHsX7v5+e4p+c4s0zhR9YNb8afZ6pMVFdDUAAIDElpeviIalvlQpLY3xF4DIi3hY+sQTT+h//a//pYqKCl1++eXKzc1VXV2d/vCHP+gPf/iDvvOd7+jqq6+e8fnWrl2rtWvXnnW8qKgolGUDMcnvt7R0ibSw2uh4s91tOsQUfWBaE1Pty8uknBwG6AAAAJK9XrvLkoIR2l02MzMy1wGAd4t4WLpixQo99dRTWr169aTjO3bs0Gc+8xndc8892rhxo7xe74zOt3btWm3evDkcpQJxw+OxVFEulZcxRR+YSpJHKi2xO0mZag8AADCZZVlKSTER2x8hNTUy1wGAd4t4WPrBD37wnMdXr16tyy67TFu2bNHBgwe1fPnyCFcGxL8zp+gPDtpT9I8fl8aYoo8E5vdLFWVSUZHkdhOSAgAATMXrjdxmsknssALAIVH148fj8Uz6cyZqa2v1+OOPa3h4WCUlJbr88suVk5MTrhKBuOHzWVq8SFow36i5RWpslPoHnK4KiAyXJRUU2F2k7GoPAAAwM1YEh02WK3LXAoAzRU1Yevz4cf3lL39Rfn6+Fi1aNOPve+GFF/TCCy+c+jolJUWbN2/WLbfcEo4ygbjj8VgqL7PXZ+zqsrtN29qkCC1FBERUslcqK5VKS6XkZEJSAACA2QgGI3ctE8FrAcCZoiIsHR0d1Ve/+lUFAgF95StfkdvtPu/35OTk6Ktf/are9773qaSkRL29vdq6dav+5V/+Rd/+9rfl9/t10003Tfn9mZmZcrn4qAo4U3a2NH++NDxsVN8wrvr6cY0EnK4qfp35oy4tLU0pKWnOFRPncnNcqqhwqajQJZeLkBRAYmC8CyDUkpMDSkuLTFtFSqpb2dlREVkASDCWMcbRBrJgMKivfe1r+tWvfqWPfexj+sY3vjGn8x06dEibNm1SZmamXn311SkHiF1dXXO6DpAIgkGjtnZ7in5Xt9PVxJ/h4QHd/KkKSdJjT9QTloaYxy0VF9lT7f1+AlLgfLKzs50uASHGeBdAKAWDRi//KXIz0AoLpBXLGcMBCK2ZjHkd/ZjGGKM777xTv/rVr3T99dfrnnvumfM5Fy1apJUrV2rHjh2qq6vTvHnzQlApkJhcLktFhVJRodTfb9TYKB1vkcbZEApRzJ9mLytRVGQvMwEAAIC5Gx6O7FJdg4MRvBgAnMGxsDQYDOqf/umf9Nxzz+naa6/VP//zP4dsmtBESjw8PByS8wGwO/OWLJGqq9kQCtHHkr1hU3k5GzYBAACEw+BQZK/H7TwApzgSlp4ZlF599dW6//77Z7RO6UyMjY1p3759sixLxcXFITkngNPO3BCqs9PeEKq9nQ2h4AzvyQ2bytiwCQAAIKz6+iJ7vdExaXDQyOdjjAcgsiIelp4ZlH7oQx/St7/97WmD0s7OTnV1dSk7O1s5OTmnjr/55ptatWqVLOv0D86xsTHdf//9ampq0pVXXqmsrKxwvhUg4eXkWMrJsTeEamySmpqkwKjTVSERZGXagX1BgdiwCQAAIAJ6ex24Zp/k80X+ugASW8TD0ocffljPPfecfD6fqqqq9P3vf/+s12zcuFFLly6VJD311FN66KGHdPvtt2vz5s2nXvPlL39ZknTJJZeosLBQfX192r59u44dO6aSkpKQrH8KYGZSUixVL5DmzzNqaZUaGuyBDRBKLsteh7S8XMpIJyAFAACIJCfC0r5ee/8EAIikiIelTU1NkqTBwUH94Ac/OOdrSktLT4WlU7npppv06quvatu2berq6pLH41FFRYU+//nP63Of+5wyMzNDXjuA6blclkqKpZJiqbvbnqLf2soUfcxNSrJUenKqvddLSAoAABBpgYDR8Ejkr0sDBgAnWMaYhMwxurq6nC4BSAgjI3ZoyhT9sw0PD+jmT1VIkh57ol4pKWkOVxRdsjLtLtKCfKbaA5EwsUEm4gfjXQCh0tVttGNn5K+b7JX+vysZBwIInZmMeR3Z4AlA4khOtqfoz6syammR6huk/gGnq0K0siQVFkqVFVJGBgNjAACAaDDo0Ph9JCCNjRl5PIwLAUQOYSmAiHC7LZWW2tOpOzqM6uqljk6nq0K0SPLY/21UlLOrPQAAQLQZHHTw2kNSRrpz1weQeAhLAURcbq6l3Fypv98OTVtapGBCLgiC1FQ7IC0pFh0DAAAAUcqJ9UpPXZuwFECEEZYCcIzfb+miZVL1AqP6BqmxURobd7oqREK6X6qqkgoLJMsiJAUAAIhmY2POXXuc+wMAEUZYCsBxycmWFlbb65o2Nkl19VIg4HRV4Zec7NPixZed+nsiyMmWqirt7mIAAADEhmDQuWsTlgKINMsYk5CTX9kdFIhe4+P2ZlC1dfYaRfFs4kdwPHdXWpIKCuyQlE2bgOg1k51BEVsY7wIIldY2o5FhZ66dnS2lpzOGBBAaMxnz0lkKIOpMbAZVUmLU1i4dOyb19TtdVXjEc0jqsqTiYjsk9fni930CAADEu8ICxnIAEgdhKYCoZVmWCgvsdS1PnDA6ekzq6XW6KpyPy5JKS+w1SVNSGFgDAAAAAGIHYSmAmJCXZykvTzrRYVRTI/X2OV0R3o2QFAAAAAAQ6whLAcSUvFxLeblSW5tRzVGpf8DpimDJnm4/f56UmkpICgAAAACIXYSlAGJSQYGl/Hyj1lbpyFFpKM43gopWhQVS9QLWJAUAAAAAxAfCUgAxy7IsFRVJBQVGjU3SsVopEHC6qsSQm2OHpOxuDwAAAACIJ4SlAGKey2WpolwqKTaqr5dq66Xxcaerik/pfmnRQiknh5AUAAAAABB/CEsBxA2Px9L8+VJpqdHhI1Jzi9MVxQ+vV6qeL5WU2B29AAAAAADEI8JSAHEnOdnSxRdJFeVGBw5KPb1OVxS7LEkVFfbmTR4PISkAAAAAIL4RlgKIWxkZltasNjp+XDp8RBodc7qi2JKdJS1ZLPn9hKQAAAAAgMRAWAogrlmWpdJSKS/P6OAhqbXN6Yqin8dtr0vKlHsAAAAAQKIhLAWQEJKTLa1YLrW3G+0/II0EnK4oOhXk292kycmEpAAAAACAxENYCiCh5OdbysqyA1O6TE/zuKXFi6WSYkJSAAAAAEDiIiwFkHCSkuwu0+Zmo/0HpfFxpytyVlamdPFFUmoqQSkAAAAAILERlgJIWMXFljIzjd7eI/X3O12NM6oqpOpq1iYFAAAAAECSXE4XAABO8vksrV0tFRc5XUlkedzSyuXSwoUWQSkAAAAAACfRWQog4bndli6+SEr3Gx064nQ14ZeaKq1aIfn9hKQAAAAAAJyJsBQATqqstJSWZrTnHWksTtcxzc6SViyXvF6CUgAAAAAA3o1p+ABwhrw8S6vfIyV7na4k9IqLpEsvISgFAAAAAGAqhKUA8C7p6XZgmprqdCWhU14mXbRMcrkISgEAAAAAmAphKQCcg89nac17JF8cBKZVFdKSxWzkBAAAAADA+RCWAsAUkpNjv8O0ssLe8R4AAAAAAJwfYSkATCM52dJ7LpFSkp2uZPbKSqVFBKUAAAAAAMwYYSkAnEdqqqVVKyW32+lKZi4/T1qy2OkqAAAAAACILYSlADAD6emWVlzsdBUz4/dLF18k1igFAAAAAGCWCEsBYIby8ixVL3C6iukleaSVyyWPh6AUAAAAAIDZIiwFgFmoqpTycp2uYmoXLZN8PoJSAAAAAAAuBGEpAMyCZVlattTu4Iw2pSVSfj5BKQAAAAAAF4qwFABmKTnZ0sJqp6uYzOtV1NUEAAAAAECsISwFgAtQUiJlpDtdxWnV86WkJLpKAQAAAACYC8JSALgAlmVp0UKnq7D5/XZ4CwAAAAAA5oawFAAuUHa2pfw8p6uwp99bFl2lAAAAAADMFWEpAMzB/HnOXj8zQ8rLJSgFAAAAACAUCEsBYA4yMizlZDt3/cpK564NAAAAAEC8ISwFgDmqKHfmuinJUkG+M9cGAAAAACAeEZYCwBzl5dnBZaSVlrJWKQAAAAAAoeRYWLp79279p//0n7RmzRqtWrVKH/3oR/XrX/96VucIBoN68skndd1112nFihVat26dvvjFL6q2tjY8RQPAOViWpbKyyF7TZUllpZG9JgAAAAAA8c6RsHTr1q36xCc+oR07duiv/uqv9B//439UV1eXvvKVr+gHP/jBjM/z9a9/Xd/4xjcUDAb1yU9+Uu9973v18ssv66Mf/aiOHDkSxncAAJOVFEuR7PEsKJC8XrpKAQAAAAAIJcsYYyJ5wbGxMX34wx9WS0uLnnnmGS1btkyS1N/fr5tuuknHjh3Tb37zG1VVVU17njfeeEM333yzVq9erZ/85Cfyer2SpNdff12f/exntXr1aj355JNTfn9XV1fI3hMASNKuN406OiNzrZXLpYICwlIAoZOd7eBudQgLxrsAAACTzWTMG/HO0jfeeEP19fW69tprTwWlkuT3+3XrrbdqbGxMzz333HnP8+yzz0qS7rjjjlNBqSStX79eGzZs0Pbt23Xs2LHQvwEAmEJ+hDZbcrmk3NzIXAsAAAAAgEQS8bB027ZtkqQNGzac9dwVV1wx6TXT2bp1q3w+ny699NKznps49/bt2+dSKgDMSl6EAszsLMntpqsUAAAAAIBQi3hYOrH5UmVl5VnPZWZmKjs7W3V1ddOeY3BwUO3t7SorK5Pb7T7r+Ykp/Gz0BCCSUlMtpaaG/zqRCmUBAAAAAEg0nkhfsL+/X5KUnp5+zuf9fr9aWlqmPUdfX9+p1051jjOvdS6ZmZlyuRzZ3wpAHKueP6ajtePhvcZCr9J8dJYCAKbHeBcAAGD2Ih6WRouenh6nSwAQhyyX0cBA+M7v9UqBkUEFRsJ3DQCJiQ2e4g/jXQAAgMmicoOnia7Pie7Qd+vv75+y63TCxPNTdY5OHJ+q8xQAwiUzI7bPDwAAAABAIot4WDqxnui51iXt6elRV1fXOdczPZPP51N+fr4aGxs1Pn72dNeJtUonrgUAkZKSYsnrDd/5M6b/LAkAAAAAAMxBxMPSNWvWSJK2bNly1nOvvfaaJGnt2rXnPc/atWs1ODioXbt2nfXcxLknrgUAkRTO7s+MzPCdGwAAAACARBfxsHT9+vUqLy/XCy+8oP3795863t/fr0ceeUQej0c33HDDqeOdnZ2qqalRZ2fnpPN87GMfkyR997vfVSAQOHX89ddf15YtW7RmzRrNmzcvzO8GAM4WzhVA0lldBAAAAACAsIn4Bk8ej0f33XefbrnlFn3iE5/QtddeK7/fr5deekmNjY264447JoWcTz31lB566CHdfvvt2rx586nj69at04033qhnn31WN9xwg9773veqo6NDv/3tb+X3+3X33XdH+q0BgCTpPMsuXzCvV0pOtsJzcgAAAAAAEPmwVLKDzqeffloPPPCAXnzxRY2Ojqq6ulpf/OIXdf3118/4PPfee68WL16sZ555Rk888YR8Pp+uuuoqfelLX6KrFIBjwrWuKOuVAgAAAAAQXpYxxjhdhBO6urqcLgFAnDLG6OV/l4LB0J63skJatJDOUgDhkZ2d7XQJCDHGuwAAAJPNZMwb8TVLASDeWZYlX2roz5sahnMCAAAAAIDTCEsBIAx8vjCck7AUAAAAAICwIiwFgDBISwv9Of3+0J8TAAAAAACcRlgKAGGQmhLa87ksKTmZ9UoBAAAAAAgnwlIACINQT8MPx7R+AAAAAAAwGWEpAIQBYSkAAAAAALGHsBQAwsDrlUI5aT45OYQnAwAAAAAA50RYCgBhYFlWSANOwlIAAAAAAMKPsBQAwsTrjc5zAQAAAACAcyMsBYAwCWXASWcpAAAAAADhR1gKAGES0s7SpNCdCwAAAAAAnBthKQCECdPwAQAAAACILYSlABAmoewGTaKzFAAAAACAsCMsBYAw8YQo4HS5JLfbCs3JAAAAAADAlAhLASBMQtVZynqlAAAAAABEBmEpAIRJqKbOMwUfAAAAAIDIICwFgDAhLAUAAAAAILYQlgJAmBCWAgAAAAAQWwhLASBM3O7oOg8AAAAAAJgeYSkAhIkrRD9hQ3UeAAAAAAAwPW7BASBMLMuSFZLzhOAkAAAAAADgvAhLASCMrBD8lKWzFAAAAACAyOAWHADCyBWCrlA6SwEAAAAAiAzCUgAIo1B0hdJZCgAAAABAZHALDgDhFIrO0rmfAgAAAAAAzABhKQBEO9JSAAAAAAAigrAUAMKInBMAAAAAgNhBWAoAYWRMdJwDAAAAAACcH2EpAIRRMDj3cxCWAgAAAAAQGYSlABDlCEsBAAAAAIgMwlIAAAAAAAAAEGEpAIRVkDVLAQAAAACIGYSlABBGJgRrloZi3VMAAAAAAHB+hKUAECbGGIWiKZTOUgAAAAAAIoOwFADCJFQhJ52lAAAAAABEBmEpAIRJqEJOOksBAAAAAIgMwlIACJNQhaV0lgIAAAAAEBmEpQAQJqHqCKWzFAAAAACAyCAsBYAoR1gKAAAAAEBkEJYCQJgwDR8AAAAAgNhCWAoAYUJHKAAAAAAAscUTqQsNDg7q97//vV5++WUdOHBAzc3N8nq9WrJkiW666SZde+21szrf4sWLp3zuy1/+sv7zf/7Pcy0ZAOYkVGEpnaUAAAAAAERGxMLSHTt26Ktf/aqysrK0fv16ffCDH1RHR4d+//vf68tf/rLefPNN3XXXXbM6Z2lpqW644Yazjl966aWhKhsALlioQk46VAEAAAAAiAzLmMjchh84cECHDx/Whz70ISUlJZ06fuLECX3sYx9TU1OTnn32Wa1YsWJG51u8eLHWrl2rJ5544oLq6erquqDvA4CZ6u0z2rpt7ufJypTWrLbmfiIAmEZ2drbTJSDEGO8CAABMNpMxb8TWLF2yZImuu+66SUGpJOXl5enjH/+4JGn79u2RKgcAwi9EH0XRWQoAAAAAQGREbBr+dDweuwy32z2r7+vt7dWzzz6rjo4O5eTkaO3ataqqqgpDhQAwex6PVJA/9/P4Uud+DgAAAAAAcH6Oh6X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      "text/plain": [
       "<Figure size 1656x552 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_violin({\"a\": a, \"b\": b});"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we carry out a two sample t-test we are implicitly using a linear model that can be specified in different ways. One of these approaches is the following:\n",
    "\n",
    "### Model 1\n",
    "\n",
    "$$\n",
    "\\mu_i = \\beta_0 + \\beta_1 (i) + \\epsilon_i\n",
    "$$\n",
    "\n",
    "where $i = 0$ represents the population 1, $i = 1$ the population 2 and $\\epsilon_i$ is a random error with mean 0. If we replace the indicator variables for the two groups we have \n",
    "\n",
    "$$\n",
    "\\mu_0 = \\beta_0 + \\epsilon_i\n",
    "$$\n",
    "\n",
    "and\n",
    "\n",
    "$$\n",
    "\\mu_1 = \\beta_0 + \\beta_1 + \\epsilon_i\n",
    "$$\n",
    "\n",
    "if $\\mu_0 = \\mu_1$ then\n",
    "\n",
    "$$\n",
    "\\beta_0 + \\epsilon_i = \\beta_0 + \\beta_1 + \\epsilon_i\\\\\n",
    "$$\n",
    "$$\n",
    "\\beta_1 = 0\n",
    "$$\n",
    "\n",
    "Thus, we can see that testing whether the mean of the two populations are equal is equivalent to testing whether $\\beta_1$ is 0."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-10-25T00:46:03.954260Z",
     "start_time": "2017-10-25T00:46:03.947515Z"
    }
   },
   "source": [
    "### Analysis\n",
    "\n",
    "We start by instantiating our model and specifying the model previously described."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:14.025148Z",
     "start_time": "2019-04-13T18:22:03.635845Z"
    }
   },
   "outputs": [],
   "source": [
    "model_1 = bmb.Model(\"value ~ 1 + group\", df)\n",
    "#results_1 = model_1.fit(inference_method=\"numpyro\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_1.build()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We've only specified the formula for the model and Bambi automatically selected priors distributions and values for their parameters. We can inspect both the setup and the priors as following:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:14.093227Z",
     "start_time": "2019-04-13T18:22:14.028196Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "       Formula: value ~ 0 + group\n",
       "        Family: gaussian\n",
       "          Link: mu = identity\n",
       "  Observations: 280\n",
       "        Priors: \n",
       "    target = mu\n",
       "        Common-level effects\n",
       "            group ~ Normal(mu: [0. 0.], sigma: [12.471 12.471])\n",
       "        \n",
       "        Auxiliary parameters\n",
       "            sigma ~ HalfStudentT(nu: 4.0, sigma: 2.4686)\n",
       "------\n",
       "* To see a plot of the priors call the .plot_priors() method.\n",
       "* To see a summary or plot of the posterior pass the object returned by .fit() to az.summary() or az.plot_trace()"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:23:39.715077Z",
     "start_time": "2019-04-13T18:23:38.912684Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Sampling: [group, sigma]\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2484x552 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model_1.plot_priors();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To inspect our posterior and the sampling process we can call `az.plot_trace()`. The option `kind='rank_vlines'` gives us a variant of the rank plot that uses lines and dots and helps us to inspect the stationarity of the chains. Since there is no clear pattern or serious deviations from the horizontal lines, we can conclude the chains are stationary.\n",
    "\n",
    "<!-- I think the reasoning is too simplistic but I don't know if we should make it more complicated here -->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:16.028568Z",
     "start_time": "2019-04-13T18:22:15.017492Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_trace(results_1, kind=\"rank_vlines\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:16.089430Z",
     "start_time": "2019-04-13T18:22:16.031107Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sd</th>\n",
       "      <th>hdi_3%</th>\n",
       "      <th>hdi_97%</th>\n",
       "      <th>mcse_mean</th>\n",
       "      <th>mcse_sd</th>\n",
       "      <th>ess_bulk</th>\n",
       "      <th>ess_tail</th>\n",
       "      <th>r_hat</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>group[a]</th>\n",
       "      <td>6.018</td>\n",
       "      <td>0.182</td>\n",
       "      <td>5.658</td>\n",
       "      <td>6.352</td>\n",
       "      <td>0.003</td>\n",
       "      <td>0.003</td>\n",
       "      <td>3129.0</td>\n",
       "      <td>2850.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>group[b]</th>\n",
       "      <td>7.966</td>\n",
       "      <td>0.214</td>\n",
       "      <td>7.576</td>\n",
       "      <td>8.376</td>\n",
       "      <td>0.004</td>\n",
       "      <td>0.003</td>\n",
       "      <td>3506.0</td>\n",
       "      <td>2863.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sigma</th>\n",
       "      <td>2.287</td>\n",
       "      <td>0.100</td>\n",
       "      <td>2.102</td>\n",
       "      <td>2.474</td>\n",
       "      <td>0.002</td>\n",
       "      <td>0.002</td>\n",
       "      <td>3869.0</td>\n",
       "      <td>2757.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           mean     sd  hdi_3%  hdi_97%  mcse_mean  mcse_sd  ess_bulk  \\\n",
       "group[a]  6.018  0.182   5.658    6.352      0.003    0.003    3129.0   \n",
       "group[b]  7.966  0.214   7.576    8.376      0.004    0.003    3506.0   \n",
       "sigma     2.287  0.100   2.102    2.474      0.002    0.002    3869.0   \n",
       "\n",
       "          ess_tail  r_hat  \n",
       "group[a]    2850.0    1.0  \n",
       "group[b]    2863.0    1.0  \n",
       "sigma       2757.0    1.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "az.summary(results_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the summary table we can see the 94% highest density interval for $\\beta_1$ ranges from 1.511 to 2.499. Thus, according to the data and the model used, we conclude the difference between the two population means is somewhere between 1.2 and 2.2 and hence we support the hypotehsis that $\\beta_1 \\ne 0$.\n",
    "\n",
    "Similar conclusions can be made with the density estimate for the posterior distribution of $\\beta_1$. As seen in the table, most of the probability for the difference in the mean roughly ranges from 1.2 to 2.2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1656x552 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "az.plot_posterior(results_1, var_names=\"group\", ref_val=0);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another way to arrive to a similar conclusion is by calculating the probability that the parameter $\\beta_1 > 0$. This probability is equal to 1, telling us that the mean of the two populations are different."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:16.411144Z",
     "start_time": "2019-04-13T18:22:16.370610Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Probabiliy that posterior is > 0\n",
    "(results_1.posterior[\"group\"] > 0).mean().item()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The linear model implicit in the t-test can also be specified without an intercept term, such is the case of Model 2.\n",
    "\n",
    "### Model 2\n",
    "\n",
    "When we carry out a two sample t-test we're implicitly using the following model:\n",
    "\n",
    "$$\n",
    "\\mu_i = \\beta_i + \\epsilon_i\n",
    "$$\n",
    "\n",
    "where $i = 0$ represents the population 1, $i = 1$ the population 2 and $\\epsilon$ is a random error with mean 0. If we replace the indicator variables for the two groups we have \n",
    "\n",
    "$$\n",
    "\\mu_0 = \\beta_0 + \\epsilon\n",
    "$$\n",
    "\n",
    "and\n",
    "\n",
    "$$\n",
    "\\mu_1 = \\beta_1 + \\epsilon\n",
    "$$\n",
    "\n",
    "if $\\mu_0 = \\mu_1$ then\n",
    "\n",
    "$$\n",
    "\\beta_0 + \\epsilon = \\beta_1 + \\epsilon\\\\\n",
    "$$\n",
    "\n",
    "Thus, we can see that testing whether the mean of the two populations are equal is equivalent to testing whether $\\beta_0 = \\beta_1$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2017-10-25T00:46:03.954260Z",
     "start_time": "2017-10-25T00:46:03.947515Z"
    }
   },
   "source": [
    "### Analysis\n",
    "\n",
    "We start by instantiating our model and specifying the model previously described. In this model we will bypass the intercept that Bambi adds by default by setting it to zero, even though setting to -1 has the same effect."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:14.025148Z",
     "start_time": "2019-04-13T18:22:03.635845Z"
    }
   },
   "outputs": [],
   "source": [
    "model_2 = bmb.Model(\"Val ~ 0 + Group\", df)\n",
    "results_2 = model_2.fit() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We've only specified the formula for the model and Bambi automatically selected priors distributions and values for their parameters. We can inspect both the setup and the priors as following:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:14.093227Z",
     "start_time": "2019-04-13T18:22:14.028196Z"
    }
   },
   "outputs": [],
   "source": [
    "model_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:23:39.715077Z",
     "start_time": "2019-04-13T18:23:38.912684Z"
    }
   },
   "outputs": [],
   "source": [
    "model_2.plot_priors();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To inspect our posterior and the sampling process we can call `az.plot_trace()`. The option `kind='rank_vlines'` gives us a variant of the rank plot that uses lines and dots and helps us to inspect the stationarity of the chains. Since there is no clear pattern or serious deviations from the horizontal lines, we can conclude the chains are stationary.\n",
    "\n",
    "<!-- I think the reasoning is too simplistic but I don't know if we should make it more complicated here -->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:16.028568Z",
     "start_time": "2019-04-13T18:22:15.017492Z"
    }
   },
   "outputs": [],
   "source": [
    "az.plot_trace(results_2, kind=\"rank_vlines\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:16.089430Z",
     "start_time": "2019-04-13T18:22:16.031107Z"
    }
   },
   "outputs": [],
   "source": [
    "az.summary(results_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this summary we can observe the estimated distribution of means for each population. A simple way to compare them is subtracting one to the other. In the next plot we can se that the entirety of the distribution of differences is higher than zero and that the mean of population 2 is higher than the mean of population 1 by a mean of 2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "post_group = results_2.posterior[\"Group\"]\n",
    "diff = post_group.sel(Group_dim=\"b\") - post_group.sel(Group_dim=\"a\") \n",
    "az.plot_posterior(diff, ref_val=0);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another way to arrive to a similar conclusion is by calculating the probability that the parameter $\\beta_1 - \\beta_0 > 0$. This probability equals to 1, telling us that the mean of the two populations are different."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-04-13T18:22:16.411144Z",
     "start_time": "2019-04-13T18:22:16.370610Z"
    }
   },
   "outputs": [],
   "source": [
    "# Probabiliy that posterior is > 0\n",
    "(post_group > 0).mean().item()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext watermark\n",
    "%watermark -n -u -v -iv -w"
   ]
  }
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